Relationship between feed protein content and faeces nitrogen content in early lactation dairy cows
Notice bibliographique
Résumé
Submitted 2020-07-26 | Accepted 2020-09-02 | Available 2020-12-01 https://doi.org/10.15414/afz.2020.23.mi-fpap.313-318 The increase of milk production at the farm level requires an accurate balancing of the diet and the nitrogen supply also to minimise the possible environmental pollution deriving from dairy farming. The aim of this study was to evaluate dietary protein utilization at different crude protein (CP) levels and to predict nitrogen content in faeces on the basis of nutritional parameters and milk urea nitrogen content (MUN, mg dL -1 ). The study was conducted on three groups (A, B, C) of lactating dairy cows (8 cows per group, including Latvian Brown and Holstein Black and White breeds) from 10 to 30 days in milk. Total mixed rations containing different levels of CP (approximately 18.0%, 17.5% and 17.0% for A, B and C, respectively) were fed. The amount of feed consumed by each cow was measured and feed samples collected during the trial. Milk yield (kg d-1 -1 ) and faeces amount were recorded, and samples were collected at day 21 of the study for further analysis. Feed samples were analysed for CP, net energy for lactation (NEL, MJ kg -1 ) and other parameters. Milk samples were analysed for fat (%), total protein (%), casein (%) and urea content (mg dL -1 ). The statistical investigation was conducted using ANOVA, and correlation and regression analyses. The results showed that milk yield, fat, total protein, casein, urea, and MUN were not significantly different among groups being not affected by the dietary CP levels. The correlation between faecal nitrogen content and CP content in feed was moderately positive and statistically significant (r=0.44, P=0.03), while the correlation between faecal nitrogen content and MUN was moderately negative and showed tendency towards significance (r=-0.39, P=0.06). The regression analysis showed that feed CP explained approximately 20% of faeces nitrogen content. Keywords: dairy cow, milk urea, faeces nitrogen, feed crude protein References Amanlou, H., Farahani, T. A. and Farsuni, N. E. (2017). Effects of rumen undegradable protein supplementation on productive performance and indicators of protein and energy metabolism in Holstein fresh cows. Journal of Dairy Science, 100, 3628-3640. https://doi.org/10.3168/jds.2016-11794 J. A. D. R. N., Judy, J. V., Kebreab, E. and Kononoff, P. J. (2016). Prediction of drinking water intake by dairy cows. Journal of Dairy Science, 99, 7191–7205. https://doi.org/10.3168/jds.2016-10950 Arunvipas, P., VanLeeuwen, J. A., Dohoo, I. R., Keefe, G. P., Burton, S. A. and Lissemore, K. D. (2008). Relationships among milk urea-nitrogen, dietary parameters and fecal nitrogen in commercial dairy herds. Canadian Journal of Veterinary Research, 72, 449-453. Bijgaart, H. van den. (2003). Urea. New applications of mid-infra-red spectrometry. Bulletin of IDF, 383, 5-15. Broderick, G. and Huhtanen, P. (2020). Application of milk urea nitrogen values. Retrieved on June 30, 2020 from https://naldc.nal.usda.gov/download/15797/PDF Bucholtz, H., Johnson, T. and Eastridge, M. L. (2007). Use of milk urea nitrogen in herd management. In: Tri–State Dairy Nutrition Conference. Proceedings. Ft. Wayne, Indiana, p. 63-67. Colmenero, J. J. O. and Broderick, G. A. (2006). Effect of dietary crude protein concentration on milk production and nitrogen utilization in lactating dairy cows. Journal of Dairy Science, 89, 1704-1712. https://doi.org/10.3168/jds.S0022-0302(06)72238-X Dijkstra, J., Oenema, O. and Bannink, A. (2011). Dietary strategies to reduce N excretion from cattle: implications for methane emissions. Current Opinion in Environmental Sustainability, 3, 414-422. https://doi.org/10.1016/j.cosust.2011.07.008 Kalscheur, K. F., Vandersall, J. H., Erdman, R. A., Kohn, R. A. and Russek-Cohen, E. (1999). Effects of dietary crude protein concentration and degradability on milk production responses of early, mid, and late lactation dairy cows. Journal of Dairy Science, 82, 545-554. https://doi.org/10.3168/jds.S0022-0302(99)75266-5 Kidane, A., Overland, M., Mydland, L. T. and Prestlokken, E. (2018). Interaction between feed use efficiency and level of dietary crude protein on enteric methane emission and apparent nitrogen use efficiency with Norwegian Red dairy cows. Journal of Animal Science, 96, 3967–3982. https://doi.org/10.1093/jas/sky256 LVS. (2004). Soil improvers and growing media - Determination of nitrogen - Part 1: Modified Kjeldahl method. Latvian standard, Riga, Latvia. LVS. (2008). Soil improvers and growing media - Sample preparation for chemical and physical tests, determination of dry matter content, moisture content and laboratory compacted bulk density. Latvian standard, Riga, Latvia. Ng-Kwai-Hang, K. F., Hayes, J. F., Moxley J. E. and Monardes, H. G. (1985). Percentages of protein and nonprotein nitrogen with varying fat and somatic cells in bovine milk. Journal of Dairy Science, 68, 1257-1262. https://doi.org/10.3168/jds.s0022-0302(85)80954-1 NRC. (2001). Nutrient Requirements of Dairy Cattle: Seventh Revised Edition, 2001. Washington, DC: The National Academies Press. https://doi.org/10.17226/9825 Powell, J. M. and Rotz, C. A. (2015). Measures of nitrogen use efficiency and nitrogen loss from dairy production systems. Journal of Environmental Quality, 44, 336-344. https://doi.org/10.2134/jeq2014.07.0299 Recktenwald, E. B., Ross, D. A., Fessenden, S. W., Wall, C. J. and Van Amburgh, M. E. (2014). Urea-N recycling in lactating dairy cows fed diets with 2 different levels of dietary crude protein and starch with or without monensin. Journal of Dairy Science, 97, 1611-1622. https://doi.org/10.3168/jds.2013-7162 Rotz, C. A., Satter, L. D., Mertens, D. R. and Muck, R. E. (1999). Feeding strategy, nitrogen cycling, and profitability of dairy farms. Journal of Dairy Science, 82, 2841-2855. https://doi.org/10.3168/jds.S0022-0302(99)75542-6 Spiekers, H. and Obermaier, A. (2007). Milchhrnstoffgehalt und N-Aussheidung.L SuB Heft 4-5/07, 2007. S. III-4 bis III-8. Straalen, W. M. (1995). Modelling of nitrogen flow and extraction in dairy cows. PhD thesis. Landbouw Universiteit Wageningen. ISBN 90-5485-475-8.
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